gr_eta_lasso_fullrank

fn_eta_lasso_fullrank

current estimate of the eta parameter

current estimate of the sigma2 parameter

sigma2

current estimate of the beta parameter including the intercept.
this should be of length p+1, where p is the number of variables.

beta

non-zero eigenvalues of the kinship matrix, or the square
of the singular values of the matrix used to construct the kinship matrix

eigenvalues

input matrix, of dimension n x p; where n is the number of
observations and p are the number of predictors.

response variable. must be a quantitative variable

Used for gradient of eta. Currently being passed to optim in
 <code><a rd-options="" href="/link/lmmlasso?package=ggmix&version=0.0.2" data-mini-rdoc="ggmix::lmmlasso">lmmlasso</a></code> and used in <code><a rd-options="" href="/link/kkt_check?package=ggmix&version=0.0.2" data-mini-rdoc="ggmix::kkt_check">kkt_check</a></code>

Fit penalized multivariable linear mixed models with a single
random effect to control for population structure in genetic association
studies. The goal is to simultaneously fit many genetic variants at the
same time, in order to select markers that are independently associated
with the response. Can also handle prior annotation information,
for example, rare variants, in the form of variable weights. For more
information, see the website below and the accompanying paper:
Bhatnagar et al., "Simultaneous SNP selection and adjustment for
population structure in high dimensional prediction models", 2020,
<DOI:10.1371/journal.pgen.1008766>.

Sahir Bhatnagar

ggmix

Variable Selection in Linear Mixed Models for SNP Data

Karim Oualkacha

Yi Yang

Celia Greenwood

gr_eta_lasso_fullrank function

Used for gradient of eta. Currently being passed to optim in
 <code><a rd-options='' href='lmmlasso'>lmmlasso</a></code> and used in <code><a rd-options='' href='kkt_check'>kkt_check</a></code>

gr_eta_lasso_fullrank: Functions related to eta parameter used in optim and kkt checks

Description

Usage

Arguments

Value

See Also